![]() Related Article: What you should know about Historical Data in Web Analytics Tip #3: Select the right time period to analyse your data trends Rule #2: The more you look at the data in an aggregate form, the bigger should be your time frame for historical analysis. Rule #1: The more you segment your data, the smaller should be your time frame for historical analysis. So comparing one year of web analytics data to the last year could be like comparing apples to oranges because so much would have changed during that time from website size, traffic, products, competitors to your target market. The older the data, the more unreliable it becomes. This is because we live and operate in a constant change of marketing conditions, trends, buying behavior, pricing, competition, and multi-channel funnels. The insight you get from analyzing historical data is often out of date, and it does not always match the present marketing conditions. Tip #2: Understand that historical data is in fact “dated” If you are not sure how the data has been collected or can’t purge it, avoid taking major business decisions based on such data.Ĭollect fresh data and then wait for at least 3 months before you start analysing data trends. Often wrong goals, incorrect goal values, incorrect ROI calculations, incorrect installation of tracking codes, etc., can corrupt the data.Īny decision made based on corrupted data could prove fatal for your marketing efforts and business. for the time period you have chosen to analyse. Tip #1: Always question how the data is collectedīefore you analyse and interpret any data, always make sure that the data has been collected as accurately as possible esp. I am going to highlight a few key tips which I follow while analysing ‘data trends’ to get the highest possible ROI from my campaigns: One wrong interpretation and you can lose hundreds of thousands of dollars (depending upon the size of your business). How you analyse and interpret the ‘data trends’ plays a very important role in optimizing your marketing campaigns and making predictions about future outcomes. In trend analysis, we spot a pattern(s), interpret it and then make predictions based on historical data. Which is the most effective marketing channel in terms of goal conversions and revenue?.Where should I invest my money and resources to get the highest possible ROI?.Is the average order value improving or deteriorating over time?. ![]() Are website sales growing over time or declining?.Is the performance of a marketing channel, campaign, traffic source, metric, etc., improving or deteriorating over time?.We do trend analysis to get answers to questions like: We do trend analysis to measure the performance of a marketing channel, traffic source, campaign or metric over time. What is the advantage of doing trend analysis in Google Analytics? #2 The ‘average order value’ has steadily declined since Feb 2018. #1 The ‘ecommerce conversion rate’ went up between Jan and May 2018, and then there was a sharp decline. The screenshot above shows a trend for ‘ ecommerce conversion rate‘ and ‘average order value’ between Jan 1 and June 30, 2018.įrom the screenshot, we can conclude the following:
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